We’d love to hear from you if you are looking for:
- Start-up energy working with a brilliant and passionate team
- $300 billion market opportunity
- Exponential growth (6 straight quarters of 50-100%+ quarter over quarter growth)
- Open communication environment based on high integrity values
- Rockstar teammates. You will be working with a strong team with prior work experience at Amazon, Microsoft, Alibaba, Nivida, Huawei, etc.
Jerry.ai is building the first financial platform for your car that helps people optimize the cost and experience of owning a car (making ownership easy & affordable). We have started with helping people optimize the cost of car insurance and our vision is to help people in every aspect of car ownership. Since our product launch, we have been growing really fast for the past 18 months and our users love the product (rating 4.5 in the app store).
Jerry.ai is founded by serial entrepreneurs who previously built and scaled YourMechanic (“Uber for car repair,” the nation’s largest on-demand car repair company). We are based in Silicon Valley and have offices in Palo Alto, Toronto, and Buffalo. We are backed by Y-combinator, SV Angel, Funders Club, and many other prominent Silicon Valley Investors.
A few examples of the projects that we are working on:
- Create a smart prediction engine for customer's insurance coverage needs
- Build predictive models on customer purchase behavior based on a large data set
- Use telematics tracking to build customer driving risk profile
- Managing our ETL pipelines
- Business Intelligence:
- Determine and procure tooling/platform
- BI request workflow (business need -> report)
- Version control of queries/dashboards
- Determine and maintain correctness of data (data quality)
- Machine Learning:
- Select and deploy a platform for ML
- Determine architecture for Jerry interacting with and utilizing the ML output in business logic (i.e. APIs, etc)
- Take MVP model built by data scientist and ‘productize’ it (i.e. implement/integrate it in production system)
- Reports on the performance of deployed ML models
- B.S. or M.S. in a quantitative field required. PhD in similar fields a plus.
- Proficient in SQL, especially with Postgres dialect.
- Expertise in at least one programming language for implementing ML models and corresponding client APIs. Familiarity with NodeJS (our product dev language) is a plus.
- Experience in packaging and deploying ML code in production environments. Experience with Docker required. Experience with Kubernetes is a plus.
- Experience with BI software (preferably Metabase, Qlikview or Tableau).
- Experience with deploying and maintaining data infrastructure in the cloud (experience with AWS Lambda -> AWS Kinesis -> AWS Redshift -> Metabase BI & AWS RDS preferred)
- Comfortable working directly with data analytics to bridge business requirements with data engineering